Information Cascades in Decentralized Autonomous Organizations (DAOs)

Abstract

We examine how information cascades influence voting behavior and market performance in decentralized autonomous organizations (DAOs). Building on cascade and signaling theory, we argue that early voters and influential tokenholders disproportionately shape subsequent community decisions, especially in high-uncertainty contexts. However, we identify critical moderating factors—community intensity, token market performance, scammer prevalence, and decentralized ownership—that alter cascade dynamics and their ultimate informational quality. While strong initial cascades positively signal confidence and increase market outcomes, their beneficial effects depend crucially upon community characteristics and ownership structure. Our insights highlight conditions under which cascades effectively improve collective governance and DAO success.

Keywords: Social learning, information cascades, decentralized autonomous organization (DAO), entrepreneurial finance D26